Health co-benefits and risks of public health adaptation strategies to climate change: a review of current literature

OBJECTIVES: Many public health adaptation strategies have been identified in response to climate change. This report reviews current literature on health co-benefits and risks of these strategies to gain a better understanding of how they may affect health. METHODS: A literature review was conducted electronically using English language literature from January 2000 to March 2012. Of 812 articles identified, 22 peer-reviewed articles that directly addressed health co-benefits or risks of adaptation were included in the review. RESULTS: The co-benefits and risks identified in the literature most commonly relate to improvements in health associated with adaptation actions that affect social capital and urban design. Health co-benefits of improvements in social capital have positive influences on mental health, independently of other determinants. Risks included reinforcing existing misconceptions regarding health. Health co-benefits of urban design strategies included reduced obesity, cardiovascular disease and improved mental health through increased physical activity, cooling spaces (e.g., shaded areas), and social connectivity. Risks included pollen allergies with increased urban green space, and adverse health effects from heat events through the use of air conditioning. CONCLUSIONS: Due to the current limited understanding of the full impacts of the wide range of existing climate change adaptation strategies, further research should focus on both unintended positive and negative consequences of public health adaptation

Development of key indicators to quantify the health impacts of climate change on Canadians

OBJECTIVES: This study aimed at developing a list of key human health indicators for quantifying the health impacts of climate change in Canada. METHODS: A literature review was conducted in OVID Medline to identify health morbidity and mortality indicators currently used to quantify climate change impacts. Public health frameworks and other studies of climate change indicators were reviewed to identify criteria with which to evaluate the list of proposed key indicators and a rating scale was developed. Total scores for each indicator were calculated based on the rating scale. RESULTS: A total of 77 health indicators were identified from the literature. After evaluation using the chosen criteria, 8 indicators were identified as the best for use. They include excess daily all-cause mortality due to heat, premature deaths due to air pollution (ozone and particulate matter 2.5), preventable deaths from climate change, disability-adjusted life years lost from climate change, daily all-cause mortality, daily non-accidental mortality, West Nile Disease incidence, and Lyme borreliosis incidence. CONCLUSIONS: There is need for further data and research related to health effect quantification in the area of climate change. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00038-013-0499-5) contains supplementary material, which is available to authorized users

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Fine-Scale Mapping of the 4q24 Locus Identifies Two Independent Loci Associated with Breast Cancer Risk

Background: A recent association study identified a common variant (rs9790517) at 4q24 to be associated with breast cancer risk. Independent association signals and potential functional variants in this locus have not been explored. Methods: We conducted a fine-mapping analysis in 55,540 breast cancer cases and 51,168 controls from the Breast Cancer Association Consortium. Results: Conditional analyses identified two independent association signals among women of European ancestry, represented by rs9790517 [conditional P = 2.51 × 10−4; OR, 1.04; 95% confidence interval (CI), 1.02–1.07] and rs77928427 (P = 1.86 × 10−4; OR, 1.04; 95% CI, 1.02–1.07). Functional annotation using data from the Encyclopedia of DNA Elements (ENCODE) project revealed two putative functional variants, rs62331150 and rs73838678 in linkage disequilibrium (LD) with rs9790517 (r2 ≥ 0.90) residing in the active promoter or enhancer, respectively, of the nearest gene, TET2. Both variants are located in DNase I hypersensitivity and transcription factor–binding sites. Using data from both The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), we showed that rs62331150 was associated with level of expression of TET2 in breast normal and tumor tissue. Conclusion: Our study identified two independent association signals at 4q24 in relation to breast cancer risk and suggested that observed association in this locus may be mediated through the regulation of TET2. Impact: Fine-mapping study with large sample size warranted for identification of independent loci for breast cancer risk

Author Correction: Comprehensive analysis of chromothripsis in 2,658 human cancers using whole-genome sequencing

Correction to: Nature Genetics, published online 05 February 2020. In the published version of this paper, the members of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium were listed in the Supplementary Information; however, these members should have been included in the main paper. The original Article has been corrected to include the members and affiliations of the PCAWG Consortium in the main paper; the corrections have been made to the HTML version of the Article but not the PDF version. Additional corrections to affiliations have been made to the PDF and HTML versions of the original Article for consistency of information between the PCAWG list and the main paper

Relative Industry Concentration and Customer-Driven IT Spillovers

We examine how one industry's productivity is affected by the IT capital of its customers and how this effect depends on industries' relative concentration. These customer-driven IT spillovers result from customers' IT investments in various information systems that reduce transaction costs through information sharing and coordination and lead to more efficient production and logistics upstream. The magnitude of IT spillovers depends on relative industry concentration because customers in more concentrated industries relative to those of their suppliers are better able to retain the benefits from their IT investments. We model customer-driven effects based on production theory and empirically test the model using two industry-level data sets covering different and overlapping time periods (1987-1999 and 1998-2005), different scopes of the economy (manufacturing only versus all industries), and different levels of industry aggregation. We find that, given an increase in a downstream industry's IT capital, there is a significant increase in downstream industry output as well as significant increases in upstream industry output. Moreover, the magnitude of IT spillovers is related to relative industry concentration: A 1% decrease in a customer's relative industry concentration increases spillovers by roughly 1%. Thus, further increases in IT capital can be justified along the supply chain, and an industry's relative concentration-which can reflect market power-in part determines the distribution of productivity benefits.School of Accounting and Financ

Health related quality of life measured by SF-36: a population-based study in Shanghai, China

<p>Abstract</p> <p>Background</p> <p>Health related quality of life (HRQL) is a research topic that has attracted increasing interests around the world over the past two decades. The 36-item Short Form (SF-36) is a commonly used instrument for measuring HRQL. However, the information on Chinese adults' quality of life is limited. This paper reports on the feasibility of using the Mandarin version of SF-36 to evaluate HRQL in the population of Shanghai, China.</p> <p>Methods</p> <p>A total of 1034 subjects were randomly sampled using a stratified multiple-stage sampling method in Shanghai. Demographic information was collected, and SF-36 was used to measure HRQL.</p> <p>Results</p> <p>Internal reliability coefficients were greater than 0.7 in six of the eight SF-36 dimensions, except social function and mental health. Intraclass correlation coefficients ranged from 0.689 to 0.972. Split-half reliability coefficients were higher than 0.9 in five SF-36 dimensions. Validity was assessed by factor analysis and correlation analysis. Our results were basically in accordance with the theoretical construction of SF-36. The average scores of most SF-36 dimensions were higher than 80. The primary influencing risk factors of HRQL included chronic diseases, age, frequency of activities, and geographical region, which were identified using multivariate stepwise regression.</p> <p>Conclusion</p> <p>Overall, HRQL in the population of Shanghai is quite good. The Mandarin version of SF-36 is a valid and reliable tool for assessing HRQL.</p